With the advancement of increased computing power, face recognition applications are becoming more and more popular, e.g., Auto focus/Auto white balance/Auto exposure (3A) processing and smile shutter in digital cameras, avatar-based communications on smart phones, face recognition login capabilities on handheld computing devices, and so on. In these facial analysis applications, it may be desirable to detect facial attributes. Facial attributes may include whether a face is smiling or not, whether a face is the face of as man or a woman, whether the eyes are closed or not, or whether a face belongs to a child, young adult, middle aged adult, or a senior citizen. Other facial attributes may also be detected. Facial attribute detection has many usages. For instance, smile detection can be used as a smile shutter activation in camera imaging, or used as a mood detection capability in an automated favorite advertising survey. Gender detection can be used in automated advertising selection for smart digital signage. Facial attribute detection can also be used in other areas such as video surveillance, visual search, and content analysis, etc. Thus, fast and efficient techniques for detection of facial attributes in facial images are desired.